Cheaper than big cloud, straighter than RunPod: rent a GPU with per-second billing, a hard budget cap and the promise that you don't pay for seconds that don't work — or put your own idle card up for rent.
No commitment: you pay by the second and stop whenever you want. The product is in Phase 0 — there is no public sign-up flow yet, and the console runs on a local development address.
If a node fails its health check, billing stops that same second and your job moves to another host from its checkpoint. On any day you were charged for a broken pod, we refund the difference — without being asked.
Set your monthly limit; when the ceiling is reached, jobs pause safely. Every line item — including the storage charge on a stopped pod — sits on one screen. "Surprise invoice" is not a category here.
Not per minute, and certainly not per hour: you pay for the seconds you use. Start-up takes under two minutes, shutdown is one click, commitment is zero.
These three points are the product's commitment, not a report of past performance: the metering and the health gate are one of Phase 0's delivery slices and are not running in production yet. Component-by-component status: Status.
Starting templates
Nobody wants an empty GPU; they want something that runs. A template is one image plus sane defaults — disk, ports, a recommended GPU. Pick one here and the console opens its rent dialog with that template already selected. Per-second billing starts when the pod does.
Experiment and prototype: from a notebook cell to a training script, without changing machines.
Publish a model as an API; on the client side only base_url changes.
Pull an open model and run it with a single command; the pod answers on an endpoint that is yours.
LoRA, QLoRA and full fine-tune recipes; checkpoints land on a volume that outlives the pod.
SD/SDXL/Flux workflows on a node-based interface. Preparing: the template package is not fixed yet — today the same work runs through the custom-image flow, you just supply the image.
Transcription, subtitles and batch audio processing. Preparing: the template package is not fixed yet — today it runs through the custom-image flow, you just supply the image.
3D render, animation and architectural visualization. Preparing: the template package is not fixed yet — today it runs through the custom-image flow, you just supply the image.
Tool-calling LLM agents and long-running jobs. Preparing: the template package is not fixed yet — today it runs through the custom-image flow, you just supply the image.
Your own container: paste the registry address, set the disk and the ports, start. Every workload the list above does not cover lands here.
Four of the templates run today with public, official images and the custom image always works; the other four are marked preparing — their package is not fixed yet, so their Start button hands you the custom-image flow and you supply the image. Nothing here carries a "ready" label before it is ready. Image tags are deliberately not printed on this page: tags move, and a stale page is worse than no page — the exact image sits in the console's rent dialog. Full list: Model Catalog.
Workloads
The list is short on purpose: it covers the work people actually run on a rented GPU. Where a template is still preparing, the work itself is possible today anyway — with your own image. Nothing below promises more than that.
By workload, in more depth: fine-tuning · inference · image & video. Console links point to a local development address.
For people who live in code
One API key to search offers, spin up a pod and open an endpoint. A CLI, a Python SDK and OpenAI-compatible endpoints exist from day one — they live inside your infrastructure code, not in browser tabs.
Serverless Inference
Paste a Hugging Face model name and get a production endpoint that scales to zero, with a cold-start target under 2 seconds. No requests, no charge — the marketplace carries the cost of the waiting GPU, not you.
Cold-start target: image pre-pull plus a model cache on the host's NVMe. No user stuck in a queue, no endpoint burning money.
When traffic stops the endpoint sleeps, and so does its bill. It wakes on the first request — no standby replica required.
OpenAI-compatible API: bring your current client, your LangChain setup, your agent as they are. The only line that changes is base_url.
Serverless inference belongs to Phase 2: there is no endpoint you can open today, and the numbers above are targets — not measured results. Detail: Serverless Inference.
Sovereign Region
Pin your pod to a country; your data does not cross that border. We work through EU and Turkish legal entities — we are not a structure from which data can be demanded under the US CLOUD Act. The AI Act is in force and KVKK (Turkish personal data protection law) is on the table: your compliance team's sign-off is the easy part.
The list above is of targeted regions; being able to select a region does not mean a machine is available there at that moment. SOC 2 Type I has not been obtained — the process stands as a goal to be started in Phase 3. Detail: Sovereignty.
Pricing
Hosts set the prices and competition pushes them down; we take a 15% commission and we do not hide it. Below are example starting prices from today's pool — the live ones are in the console.
| GPU | VRAM | Typical use | Starting price |
|---|---|---|---|
| RTX 3090 | 24 GB | Stable Diffusion, small LLMs | $0.21/hr |
| RTX 4090 | 24 GB | Fine-tuning, image generation | $0.42/hr |
| L40S | 48 GB | Inference, video | $0.79/hr |
| RTX A6000 | 48 GB | Long context, render | $0.88/hr |
| A100 PCIe | 80 GB | Training, 70B inference | $1.32/hr |
| H100 SXM | 80 GB | Serious training runs | $2.19/hr |
These are example prices; on the marketplace they move second by second with supply and demand. Storage and traffic are separate, visible line items — tracked with a live counter on the billing screen.
Become a Host
A rig left over from mining, your studio's render farm or your university cluster — install one binary and join the pool without opening an inbound port. Commission is 15% (the industry is known to sit in the 20–25% band), payouts are weekly, and the scorecard is public: a good host gets more work.
The host agent, machine registration and weekly payouts go live in Phase 1; there is no open application form today.
Illustrative calculation: the price and the utilization are assumptions, not measured earnings.
Frequently Asked
That is exactly what the scorecard is for: every host is benchmarked continuously, its score is public, and critical work is not placed on a low-scoring machine. For enterprise work there is a "Verified" tier with on-site audits and an SLA. And the guarantee holds either way: seconds that don't work are not billed.
Three things: a broken node does not run up a bill (automatic detection + refund + the job moves), the invoice sits on one screen with a hard cap (the storage charge on a stopped pod is no surprise), and our EU + TR legal structure lets us pin data to a region — we do not fall under the US CLOUD Act.
Secrets never land on the host's disk; images are signed, sensitive workloads are placed only on the Verified tier, and your persistent data sits in encrypted, S3-compatible storage. The host cannot see inside your container.
It does not: the job is paused safely, its checkpoint is kept and a notification reaches you. Raise the limit and continue from the second you left off. The cap is a brake, not a guillotine.
Get started
The console and the API contract were written in Phase 0; there is no public sign-up flow yet. What there is to look at today is the code and the roadmap.
Console links point to the console domain; when you open the site locally they are rewritten to localhost:3000.